Statistics (the Easier Way) with R

Designed for beginning and intermediate data scientists, graduate students beginning research, undergraduate students taking a first or second applied statistics class, quality improvement professionals, and consultants, this unique book provides an integrated treatment of statistical inference tech [...]
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Designed for beginning and intermediate data scientists, graduate students beginning research, undergraduate students taking a first or second applied statistics class, quality improvement professionals, and consultants, this unique book provides an integrated treatment of statistical inference techniques in data analysis. Each example is solved analytically, then computationally (using the R Statistical Software) so that readers can see exactly how the computations are performed. Each technique is framed within an easy-to-apply 7 Step methodology that will make planning and presenting research a breeze. If you're new to statistics, data science, or R, this book will help you get started. If you have some experience already, this book will make you more productive and enhance your understanding of foundational statistical concepts including one and two-sample t-tests, paired t-test, one and two proportion z-test, Chi-square test of independence, one-way ANOVA, and inference for linear regression.